SlideShare a Scribd company logo
1 of 33
Download to read offline
Microsatellites
What is microsatellite
• Simple Sequence Repeats (SSR)
• 1-6 bp long
Classification of Microsatellites

• Simple microsatelltes
• Composite microsatellites
(GT)n (AC)n (AG)n

Simple
microsatellites
contain
only
one
kind
of
repeat
sequences:
Composite
microsatellites
contain
more
than
one
type
repeats
Molecular Basis of Microsatellite
Polymorphism

Different by 3 repeats

• Slippage of DNA polymerase is believed to be the major cause of
microsatellite variation
• The mutation rate can be as high as 0.1 to 0.2% per generation
Abundant and Even Distribution
Abundant
•

Abundance varies with species, but all species
studied to date have miocrosatellites
• In well studied mammal species, one
microsatellite exist in every 30-40 kb DNA.
Even distribution
•
•
•
•
•
•

On all chromosomes
On all segments of chromosomes
With genes
Often in introns
In exons as well
Trinucleotide repeats and human diseases:
Huntington disease, fragile X, and other mental
retardation-related human diseases
Small Locus sizes adapt them for PCR

PCR
2
6 3
1
Microsatellites are co-dominant
markers
AB

BC

CD

BC

AD

BD

Allele A

Allele B
Allele C
Allele D

CC

CD

AC

AB

BD

AC

BD

AB
Mendelian Inheritance of Microsatellites

Microsatellites are inherited as codominant markers according
to Mendelian laws
Liu et al. 1999. Biochem. Biophys. Res Comm. 259: 190-194
Liu et al. 1999. J. Heredity 90: 307-311.
Advantages of Microsatellite Markers

Abundant

Evenly
distributed

Highly
polymorphic

Co-dominant

Small
loci
Development of
microsatellite markers
Need

•
•

SSR containing clones
Sequences of the flanking regions of SSR
Microsatellites-enriched
Small-insert DNA Libraries (I)
Genomic DNA
Digest with several 4-bp blunt enders
Gel fraction of 300-600 bp
Ligation to a phagemid vector
insert

insert

insert

insert

micro
Small insert
3.5 kb

insert

Small insert
3.4 kb

Small insert
Small insert

Small insert

Small insert

3.4 kb

3.4 kb

3.4 kb

insert

Small insert
3.4 kb

insert

Small insert
3.4 kb

insert

Small insert
3.4 kb

3.4 kb

insert

Small insert
3.4 kb
Microsatellites-enriched Libraries (II)
micro
insert

insert

Small insert plasmids
3.5 kb

Small insert plasmids
3.5 kb

insert

in sert

Small insert plasmids
3.5 kb

Small insert plasmids
3.5 kb

Using dut/ungCJ236 strain
u
u

u

Single-stranded phagemids
3.5 kb

Conversion into single-stranded
phagemids using helper phage
u
micro u
u
u
u
u
u
u
u
u
Single-stranded phagemids
Single-stranded phagemids
Single-stranded phagemids
3.5 kb

3.5 kb

Won’t be converted to ds
will be degraded in WT host

3.5 kb
Microsatellite-enriched Libraries (III)
micro

Convert into ds

micro

u micro
ds plasmids

using (CA)15 (e.g.)
Single-stranded phagemids
3.5 kb

u

Transform into
WT E. coli

u
3.5 kb
3.5 kb

micro
ds plasmids
3.5 kb

According to Ostrander et al., 1992: PNAS 89:3419
Microsatellites-enriched
Libraries

CA
GA
TA
CG
CT
GT

CAA
CAT
CAG
CAC
CGG
CGT
CGC
CGA
...

4 bp

5 bp
Characterization
of Microsatellites
• Isolate plasmid DNA;
• sequence clones;
• Identify clones with enough sequences
for primer design.
PCR Optimization and PIC Analysis
• PCR products best <200 bp
• PCR conditions: annealing temperature, Mg++, pH,
DMSO, etc.
• Polymorphism information content
• Polymorphism in reference families
Disadvantages of microsatellites
• Previous genetic information is needed
• Huge Upfront work required
• Problems associated with PCR of microsatellites
The concept of Polymorphic
information content
• Measures the usefulness of a marker
• Informativeness in specific families
Microsatellite Genotyping

1. AA x AA

Not polymorphic

2. AA x BB

No segregation

3. AØ x ØØ

Only 1 allele
segregating 1:1

4. AA x AB

B segregates 1:1,
A segregates with intensity 1:1

5. AA x BØ

A not segregate
B segregates 1:1

6. AØ x AB

A segregates 3:1,
B segregates 1:1

7. AB x AB

A segregates 3:1,
B segregates 3:1
Microsatellite Genotyping

8. AØ x BØ

A segregates 1:1,
B segregates 1:1

9. AB x ØØ

A segregates 1:1, B segregates
1:1, A & B alternating

10. AA x BC

2 of the 3 alleles
segregating 1:1

11. AØ x BC

All 3 alleles segregating 1:1,
2 types with only 1 allele

12. AB x AC

2 of 3 alleles segregating 1:1,
the other 3:1 with a single allele
existing for some individuals

13. AB x CD

All 4 alleles
segregating 1:1
Polymorphic Information Content PIC)
•

PIC refers to the value of a marker for detecting
polymorphism within a population
• PIC depends on the number of detectable alleles
and the distribution of their frequency.
• Bostein et al. (1980) Am. J. Hum Genet. 32:314331.
• Anderson et al. (1993). Genome 36: 181-186.
Polymorphic Information Content (PIC)

n
PICi = 1-∑ Pij2
j=1
Where PICi is the polymorphic information content
of a marker i; Pij is the frequency
of the jth pattern for marker i and the summation
extends over n patterns
Polymorphic Information Content PIC)

n
PICi = 1-∑ Pij2
j=1
Example: Marker A has two alleles, first allele has a
frequency of 30%, the second allele has a
frequency of 70%
PICa = 1- (0.32 + 0.72) = 1- (0.09 + 0.49) = 0.42
Polymorphic Information Content PIC)

n
PICi = 1-∑ Pij2
j=1
Example: Marker B has two alleles, first allele has a
frequency of 50%, the second allele has a
frequency of 50%
PICb = 1- (0.52 + 0.52) = 1- (0.25 + 0.25) = 0.5
Polymorphic Information Content PIC)

n
PICi = 1-∑ Pij2
j=1
Example: Marker C has two alleles, first allele has a
frequency of 90%, the second allele has a
frequency of 10%
PICc = 1- (0.92 + 0.12) = 1- (0.81 + 0.01) = 0.18
Polymorphic Information Content PIC)

n
PICi = 1-∑ Pij2
j=1
Example: Marker D has 10 alleles, each allele has a
frequency of 10%
PICd = 1- [10 x 0.12] = 1- 0.1 = 0.9
Allele frequency and Forensics

• Say, we have 10 marker loci
• We have done adequate population genetics to
know each one have a 10% distribution
• Test of each locus can define certain level of
confidence as to what the probability is to obtain
the results you are obtaining.
Allele frequency and Forensics
• Locus 1, positive
• You are included, but every one out of 10 people
has the chance to be positive
• locus 2, positive
• You are included, but every one out of 100
people has the chance to be positive at both
locus 1 and locus 2
• …
• Locus 10, also posive
• ...

More Related Content

What's hot

How to submit a sequence in NCBI
How to submit a sequence in NCBIHow to submit a sequence in NCBI
How to submit a sequence in NCBIMinhaz Ahmed
 
Sequenced taged sites (sts)
Sequenced taged sites (sts)Sequenced taged sites (sts)
Sequenced taged sites (sts)DHANRAJ GIRIMAL
 
protein sequence analysis
protein sequence analysisprotein sequence analysis
protein sequence analysisRamikaSingla
 
MULTIPLE SEQUENCE ALIGNMENT
MULTIPLE  SEQUENCE  ALIGNMENTMULTIPLE  SEQUENCE  ALIGNMENT
MULTIPLE SEQUENCE ALIGNMENTMariya Raju
 
Snp and its role in diseases
Snp and its role in diseasesSnp and its role in diseases
Snp and its role in diseasesAshfaq Ahmad
 
Genetic diversity clustering and AMOVA
Genetic diversityclustering and AMOVAGenetic diversityclustering and AMOVA
Genetic diversity clustering and AMOVAFAO
 
Transcriptomics and metabolomics
Transcriptomics and metabolomicsTranscriptomics and metabolomics
Transcriptomics and metabolomicsSukhjinder Singh
 
Genome wide association studies seminar
Genome wide association studies seminarGenome wide association studies seminar
Genome wide association studies seminarVarsha Gayatonde
 
sequence alignment
sequence alignmentsequence alignment
sequence alignmentammar kareem
 
Quantitative trait loci (QTL) analysis and its applications in plant breeding
Quantitative trait loci (QTL) analysis and its applications in plant breedingQuantitative trait loci (QTL) analysis and its applications in plant breeding
Quantitative trait loci (QTL) analysis and its applications in plant breedingPGS
 
Prokaryotic and eukaryotic genome
Prokaryotic and eukaryotic genomeProkaryotic and eukaryotic genome
Prokaryotic and eukaryotic genomeShreya Feliz
 
Microarray (DNA and SNP microarray)
Microarray (DNA and SNP microarray)Microarray (DNA and SNP microarray)
Microarray (DNA and SNP microarray)Hamza Khan
 
Lectut btn-202-ppt-l20. genomic and c dna libraries
Lectut btn-202-ppt-l20. genomic and c dna librariesLectut btn-202-ppt-l20. genomic and c dna libraries
Lectut btn-202-ppt-l20. genomic and c dna librariesRishabh Jain
 
Hardy-Weinberg Equilibrium
Hardy-Weinberg EquilibriumHardy-Weinberg Equilibrium
Hardy-Weinberg EquilibriumVaishnovi Sekar
 
Phylogenetic tree and its construction and phylogeny of
Phylogenetic tree and its construction and phylogeny ofPhylogenetic tree and its construction and phylogeny of
Phylogenetic tree and its construction and phylogeny ofbhavnesthakur
 
Chromosome walking
Chromosome walkingChromosome walking
Chromosome walkingAleena Khan
 

What's hot (20)

How to submit a sequence in NCBI
How to submit a sequence in NCBIHow to submit a sequence in NCBI
How to submit a sequence in NCBI
 
Sequenced taged sites (sts)
Sequenced taged sites (sts)Sequenced taged sites (sts)
Sequenced taged sites (sts)
 
protein sequence analysis
protein sequence analysisprotein sequence analysis
protein sequence analysis
 
MULTIPLE SEQUENCE ALIGNMENT
MULTIPLE  SEQUENCE  ALIGNMENTMULTIPLE  SEQUENCE  ALIGNMENT
MULTIPLE SEQUENCE ALIGNMENT
 
Genome annotation
Genome annotationGenome annotation
Genome annotation
 
MICROARRAY
MICROARRAYMICROARRAY
MICROARRAY
 
Snp and its role in diseases
Snp and its role in diseasesSnp and its role in diseases
Snp and its role in diseases
 
Genetic diversity clustering and AMOVA
Genetic diversityclustering and AMOVAGenetic diversityclustering and AMOVA
Genetic diversity clustering and AMOVA
 
Transcriptomics and metabolomics
Transcriptomics and metabolomicsTranscriptomics and metabolomics
Transcriptomics and metabolomics
 
Genome wide association studies seminar
Genome wide association studies seminarGenome wide association studies seminar
Genome wide association studies seminar
 
sequence alignment
sequence alignmentsequence alignment
sequence alignment
 
Basic Steps of the NGS Method
Basic Steps of the NGS MethodBasic Steps of the NGS Method
Basic Steps of the NGS Method
 
Quantitative trait loci (QTL) analysis and its applications in plant breeding
Quantitative trait loci (QTL) analysis and its applications in plant breedingQuantitative trait loci (QTL) analysis and its applications in plant breeding
Quantitative trait loci (QTL) analysis and its applications in plant breeding
 
SNP
SNPSNP
SNP
 
Prokaryotic and eukaryotic genome
Prokaryotic and eukaryotic genomeProkaryotic and eukaryotic genome
Prokaryotic and eukaryotic genome
 
Microarray (DNA and SNP microarray)
Microarray (DNA and SNP microarray)Microarray (DNA and SNP microarray)
Microarray (DNA and SNP microarray)
 
Lectut btn-202-ppt-l20. genomic and c dna libraries
Lectut btn-202-ppt-l20. genomic and c dna librariesLectut btn-202-ppt-l20. genomic and c dna libraries
Lectut btn-202-ppt-l20. genomic and c dna libraries
 
Hardy-Weinberg Equilibrium
Hardy-Weinberg EquilibriumHardy-Weinberg Equilibrium
Hardy-Weinberg Equilibrium
 
Phylogenetic tree and its construction and phylogeny of
Phylogenetic tree and its construction and phylogeny ofPhylogenetic tree and its construction and phylogeny of
Phylogenetic tree and its construction and phylogeny of
 
Chromosome walking
Chromosome walkingChromosome walking
Chromosome walking
 

Viewers also liked

15 molecular markers techniques
15 molecular markers techniques15 molecular markers techniques
15 molecular markers techniquesAVINASH KUSHWAHA
 
Molecular markers used in biotechnology
Molecular markers used in biotechnology Molecular markers used in biotechnology
Molecular markers used in biotechnology sana sana
 
Mapping and QTL
Mapping and QTLMapping and QTL
Mapping and QTLFAO
 
markers in plant breeding.
markers in plant breeding.markers in plant breeding.
markers in plant breeding.Alemu Abate
 
Chloroplast transformation
Chloroplast transformationChloroplast transformation
Chloroplast transformationSachin Ekatpure
 
Mitochondria and chloroplast structure and genome organisation
Mitochondria and chloroplast structure and genome organisationMitochondria and chloroplast structure and genome organisation
Mitochondria and chloroplast structure and genome organisationHemadharshini Senthill
 
Plant transformation methods
Plant transformation methodsPlant transformation methods
Plant transformation methodsMohammed Sami
 
Molecular markers types and applications
Molecular markers types and applicationsMolecular markers types and applications
Molecular markers types and applicationsFAO
 

Viewers also liked (16)

15 molecular markers techniques
15 molecular markers techniques15 molecular markers techniques
15 molecular markers techniques
 
Gene mapping ppt
Gene mapping pptGene mapping ppt
Gene mapping ppt
 
Direct Gene Transfer Methods
Direct Gene Transfer MethodsDirect Gene Transfer Methods
Direct Gene Transfer Methods
 
Molecular markers used in biotechnology
Molecular markers used in biotechnology Molecular markers used in biotechnology
Molecular markers used in biotechnology
 
chloroplast DNA
chloroplast DNAchloroplast DNA
chloroplast DNA
 
Genome Mapping
Genome MappingGenome Mapping
Genome Mapping
 
Gene transfer (2)
Gene transfer (2)Gene transfer (2)
Gene transfer (2)
 
Mapping and QTL
Mapping and QTLMapping and QTL
Mapping and QTL
 
markers in plant breeding.
markers in plant breeding.markers in plant breeding.
markers in plant breeding.
 
Chloroplast transformation
Chloroplast transformationChloroplast transformation
Chloroplast transformation
 
Mitochondria and chloroplast structure and genome organisation
Mitochondria and chloroplast structure and genome organisationMitochondria and chloroplast structure and genome organisation
Mitochondria and chloroplast structure and genome organisation
 
Plant transformation methods
Plant transformation methodsPlant transformation methods
Plant transformation methods
 
Mitochondrial dna
Mitochondrial dnaMitochondrial dna
Mitochondrial dna
 
Molecular marker
Molecular markerMolecular marker
Molecular marker
 
Molecular markers
Molecular markersMolecular markers
Molecular markers
 
Molecular markers types and applications
Molecular markers types and applicationsMolecular markers types and applications
Molecular markers types and applications
 

Similar to Microsatellites

14. marking the genome microsatellites
14. marking the genome microsatellites14. marking the genome microsatellites
14. marking the genome microsatellitesAgni Guntur S
 
Digiwest journa club presentation_18.10.2016
Digiwest journa club presentation_18.10.2016Digiwest journa club presentation_18.10.2016
Digiwest journa club presentation_18.10.2016Dhirend N. Singh
 
Lecture 10 2023Lecture 10 2023Lecture 10 2023.ppt
Lecture 10 2023Lecture 10 2023Lecture 10 2023.pptLecture 10 2023Lecture 10 2023Lecture 10 2023.ppt
Lecture 10 2023Lecture 10 2023Lecture 10 2023.pptAbdelrhman Abooda
 
PICS: Pathway Informed Classification System for cancer analysis using gene e...
PICS: Pathway Informed Classification System for cancer analysis using gene e...PICS: Pathway Informed Classification System for cancer analysis using gene e...
PICS: Pathway Informed Classification System for cancer analysis using gene e...David Craft
 
Biomarker for genotoxicity 2013
Biomarker for genotoxicity 2013Biomarker for genotoxicity 2013
Biomarker for genotoxicity 2013Elsa von Licy
 
Lecture 2 , mbbs students. pcr, rt pcr,
Lecture 2 , mbbs students. pcr, rt pcr,  Lecture 2 , mbbs students. pcr, rt pcr,
Lecture 2 , mbbs students. pcr, rt pcr, Dr Vishnu Kumar
 
PCR Webinar: COVID-19 (2020)
PCR Webinar: COVID-19 (2020)PCR Webinar: COVID-19 (2020)
PCR Webinar: COVID-19 (2020)Sijo A
 
Seftah DNA fingerprint 2007NEW.ppt
Seftah DNA fingerprint 2007NEW.pptSeftah DNA fingerprint 2007NEW.ppt
Seftah DNA fingerprint 2007NEW.pptSamerPaser
 
BIOINFORMATICS.ppt
BIOINFORMATICS.pptBIOINFORMATICS.ppt
BIOINFORMATICS.pptTSaiteja2
 
Functional genomics
Functional genomicsFunctional genomics
Functional genomicsAjit Shinde
 
Polymerase Chain Reaction (PCR) and The Application.pptx
Polymerase Chain Reaction (PCR) and The Application.pptxPolymerase Chain Reaction (PCR) and The Application.pptx
Polymerase Chain Reaction (PCR) and The Application.pptxrenanda8
 
Pcrppt biotchnological tool copy
Pcrppt  biotchnological tool   copyPcrppt  biotchnological tool   copy
Pcrppt biotchnological tool copyRajatsingh
 
Igor Segota: PhD thesis presentation
Igor Segota: PhD thesis presentationIgor Segota: PhD thesis presentation
Igor Segota: PhD thesis presentationIgorSegota3
 
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...Elia Brodsky
 

Similar to Microsatellites (20)

14. marking the genome microsatellites
14. marking the genome microsatellites14. marking the genome microsatellites
14. marking the genome microsatellites
 
Digiwest journa club presentation_18.10.2016
Digiwest journa club presentation_18.10.2016Digiwest journa club presentation_18.10.2016
Digiwest journa club presentation_18.10.2016
 
Molecular profiling 2013
Molecular profiling 2013Molecular profiling 2013
Molecular profiling 2013
 
Lecture 10 2023Lecture 10 2023Lecture 10 2023.ppt
Lecture 10 2023Lecture 10 2023Lecture 10 2023.pptLecture 10 2023Lecture 10 2023Lecture 10 2023.ppt
Lecture 10 2023Lecture 10 2023Lecture 10 2023.ppt
 
Genomics experimental-methods
Genomics experimental-methodsGenomics experimental-methods
Genomics experimental-methods
 
PICS: Pathway Informed Classification System for cancer analysis using gene e...
PICS: Pathway Informed Classification System for cancer analysis using gene e...PICS: Pathway Informed Classification System for cancer analysis using gene e...
PICS: Pathway Informed Classification System for cancer analysis using gene e...
 
Biomarker for genotoxicity 2013
Biomarker for genotoxicity 2013Biomarker for genotoxicity 2013
Biomarker for genotoxicity 2013
 
Seminar 20150920.2
Seminar 20150920.2Seminar 20150920.2
Seminar 20150920.2
 
Lecture 2 , mbbs students. pcr, rt pcr,
Lecture 2 , mbbs students. pcr, rt pcr,  Lecture 2 , mbbs students. pcr, rt pcr,
Lecture 2 , mbbs students. pcr, rt pcr,
 
PCR Webinar: COVID-19 (2020)
PCR Webinar: COVID-19 (2020)PCR Webinar: COVID-19 (2020)
PCR Webinar: COVID-19 (2020)
 
Microarrays
MicroarraysMicroarrays
Microarrays
 
Seftah DNA fingerprint 2007NEW.ppt
Seftah DNA fingerprint 2007NEW.pptSeftah DNA fingerprint 2007NEW.ppt
Seftah DNA fingerprint 2007NEW.ppt
 
BIOINFORMATICS.ppt
BIOINFORMATICS.pptBIOINFORMATICS.ppt
BIOINFORMATICS.ppt
 
Functional genomics
Functional genomicsFunctional genomics
Functional genomics
 
Polymerase Chain Reaction (PCR) and The Application.pptx
Polymerase Chain Reaction (PCR) and The Application.pptxPolymerase Chain Reaction (PCR) and The Application.pptx
Polymerase Chain Reaction (PCR) and The Application.pptx
 
Pcrppt biotchnological tool copy
Pcrppt  biotchnological tool   copyPcrppt  biotchnological tool   copy
Pcrppt biotchnological tool copy
 
Dr. Treff's Validation Presentation on EPⓖT
Dr. Treff's Validation Presentation on EPⓖTDr. Treff's Validation Presentation on EPⓖT
Dr. Treff's Validation Presentation on EPⓖT
 
PCR
PCRPCR
PCR
 
Igor Segota: PhD thesis presentation
Igor Segota: PhD thesis presentationIgor Segota: PhD thesis presentation
Igor Segota: PhD thesis presentation
 
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...
Mastering RNA-Seq (NGS Data Analysis) - A Critical Approach To Transcriptomic...
 

Recently uploaded

Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxiammrhaywood
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Celine George
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024Janet Corral
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationnomboosow
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104misteraugie
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...PsychoTech Services
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDThiyagu K
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...Sapna Thakur
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 

Recently uploaded (20)

Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communication
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 

Microsatellites

  • 2. What is microsatellite • Simple Sequence Repeats (SSR) • 1-6 bp long
  • 3. Classification of Microsatellites • Simple microsatelltes • Composite microsatellites
  • 6. Molecular Basis of Microsatellite Polymorphism Different by 3 repeats • Slippage of DNA polymerase is believed to be the major cause of microsatellite variation • The mutation rate can be as high as 0.1 to 0.2% per generation
  • 7. Abundant and Even Distribution
  • 8. Abundant • Abundance varies with species, but all species studied to date have miocrosatellites • In well studied mammal species, one microsatellite exist in every 30-40 kb DNA.
  • 9. Even distribution • • • • • • On all chromosomes On all segments of chromosomes With genes Often in introns In exons as well Trinucleotide repeats and human diseases: Huntington disease, fragile X, and other mental retardation-related human diseases
  • 10. Small Locus sizes adapt them for PCR PCR 2 6 3 1
  • 11. Microsatellites are co-dominant markers AB BC CD BC AD BD Allele A Allele B Allele C Allele D CC CD AC AB BD AC BD AB
  • 12. Mendelian Inheritance of Microsatellites Microsatellites are inherited as codominant markers according to Mendelian laws Liu et al. 1999. Biochem. Biophys. Res Comm. 259: 190-194 Liu et al. 1999. J. Heredity 90: 307-311.
  • 13. Advantages of Microsatellite Markers Abundant Evenly distributed Highly polymorphic Co-dominant Small loci
  • 15. Need • • SSR containing clones Sequences of the flanking regions of SSR
  • 16. Microsatellites-enriched Small-insert DNA Libraries (I) Genomic DNA Digest with several 4-bp blunt enders Gel fraction of 300-600 bp Ligation to a phagemid vector insert insert insert insert micro Small insert 3.5 kb insert Small insert 3.4 kb Small insert Small insert Small insert Small insert 3.4 kb 3.4 kb 3.4 kb insert Small insert 3.4 kb insert Small insert 3.4 kb insert Small insert 3.4 kb 3.4 kb insert Small insert 3.4 kb
  • 17. Microsatellites-enriched Libraries (II) micro insert insert Small insert plasmids 3.5 kb Small insert plasmids 3.5 kb insert in sert Small insert plasmids 3.5 kb Small insert plasmids 3.5 kb Using dut/ungCJ236 strain u u u Single-stranded phagemids 3.5 kb Conversion into single-stranded phagemids using helper phage u micro u u u u u u u u u Single-stranded phagemids Single-stranded phagemids Single-stranded phagemids 3.5 kb 3.5 kb Won’t be converted to ds will be degraded in WT host 3.5 kb
  • 18. Microsatellite-enriched Libraries (III) micro Convert into ds micro u micro ds plasmids using (CA)15 (e.g.) Single-stranded phagemids 3.5 kb u Transform into WT E. coli u 3.5 kb 3.5 kb micro ds plasmids 3.5 kb According to Ostrander et al., 1992: PNAS 89:3419
  • 20. Characterization of Microsatellites • Isolate plasmid DNA; • sequence clones; • Identify clones with enough sequences for primer design.
  • 21. PCR Optimization and PIC Analysis • PCR products best <200 bp • PCR conditions: annealing temperature, Mg++, pH, DMSO, etc. • Polymorphism information content • Polymorphism in reference families
  • 22. Disadvantages of microsatellites • Previous genetic information is needed • Huge Upfront work required • Problems associated with PCR of microsatellites
  • 23. The concept of Polymorphic information content • Measures the usefulness of a marker • Informativeness in specific families
  • 24. Microsatellite Genotyping 1. AA x AA Not polymorphic 2. AA x BB No segregation 3. AØ x ØØ Only 1 allele segregating 1:1 4. AA x AB B segregates 1:1, A segregates with intensity 1:1 5. AA x BØ A not segregate B segregates 1:1 6. AØ x AB A segregates 3:1, B segregates 1:1 7. AB x AB A segregates 3:1, B segregates 3:1
  • 25. Microsatellite Genotyping 8. AØ x BØ A segregates 1:1, B segregates 1:1 9. AB x ØØ A segregates 1:1, B segregates 1:1, A & B alternating 10. AA x BC 2 of the 3 alleles segregating 1:1 11. AØ x BC All 3 alleles segregating 1:1, 2 types with only 1 allele 12. AB x AC 2 of 3 alleles segregating 1:1, the other 3:1 with a single allele existing for some individuals 13. AB x CD All 4 alleles segregating 1:1
  • 26. Polymorphic Information Content PIC) • PIC refers to the value of a marker for detecting polymorphism within a population • PIC depends on the number of detectable alleles and the distribution of their frequency. • Bostein et al. (1980) Am. J. Hum Genet. 32:314331. • Anderson et al. (1993). Genome 36: 181-186.
  • 27. Polymorphic Information Content (PIC) n PICi = 1-∑ Pij2 j=1 Where PICi is the polymorphic information content of a marker i; Pij is the frequency of the jth pattern for marker i and the summation extends over n patterns
  • 28. Polymorphic Information Content PIC) n PICi = 1-∑ Pij2 j=1 Example: Marker A has two alleles, first allele has a frequency of 30%, the second allele has a frequency of 70% PICa = 1- (0.32 + 0.72) = 1- (0.09 + 0.49) = 0.42
  • 29. Polymorphic Information Content PIC) n PICi = 1-∑ Pij2 j=1 Example: Marker B has two alleles, first allele has a frequency of 50%, the second allele has a frequency of 50% PICb = 1- (0.52 + 0.52) = 1- (0.25 + 0.25) = 0.5
  • 30. Polymorphic Information Content PIC) n PICi = 1-∑ Pij2 j=1 Example: Marker C has two alleles, first allele has a frequency of 90%, the second allele has a frequency of 10% PICc = 1- (0.92 + 0.12) = 1- (0.81 + 0.01) = 0.18
  • 31. Polymorphic Information Content PIC) n PICi = 1-∑ Pij2 j=1 Example: Marker D has 10 alleles, each allele has a frequency of 10% PICd = 1- [10 x 0.12] = 1- 0.1 = 0.9
  • 32. Allele frequency and Forensics • Say, we have 10 marker loci • We have done adequate population genetics to know each one have a 10% distribution • Test of each locus can define certain level of confidence as to what the probability is to obtain the results you are obtaining.
  • 33. Allele frequency and Forensics • Locus 1, positive • You are included, but every one out of 10 people has the chance to be positive • locus 2, positive • You are included, but every one out of 100 people has the chance to be positive at both locus 1 and locus 2 • … • Locus 10, also posive • ...